Building highly effective customer service applications, in an interactive voice response (IVR) system, is complex and expensive. The value of these investments is reduced when users fail to negotiate the IVR prompts correctly, ultimately having their transaction needs met by a call center agent. When the customer is served by an agent three things occur. First, the customer is not taught how to overcome the error generated in the IVR, so they are prone to invoke the more costly agent processing of their request in a subsequent transaction. Second, the customer's preference for agent supported transactions is rewarded, hence discouraging continued use of the IVR. And third, the agent serving the IVR can be occupied with completing all of the transactions needed by the customer on that interaction with the enterprise, thus, increasing operational expenses for the center.
Currently, when users experience problems using an IVR there are three solutions. First, the most commonly applied solution is to have the call transferred to an agent, and the agent handles all the transactions associated with that call for the customer. In this model, the IVR is abandoned for the transaction where the customer is forced out or presses zero (0) to exit the IVR. Second and less frequently, an agent takes the customer's call following the failed use of the IVR and completes the transaction with which the customer struggled. If the customer has multiple transactions to complete in that call, the agent generally transfers the customer back into the IVR to complete the subsequent transactions. Finally, the least frequent occurring solution is categorized as “Agent Assisted IVR.” In this method, dedicated call center agents are concurrently listening to multiple customer interactions within the IVRs. The customer is not aware that their interaction within the IVR is being monitored. When the customer experiences a problem, the agent tries to intervene by advancing the IVR script on the caller's behalf. This method has limited application. This method provides some opportunity to improve customer IVR usage. For example, the agent responds for a customer with a heavy accent that cannot be recognized by the IVR's speech engine. The heavy accent is, however, discernible by the monitoring agent, and the agent can “push” the call along to the appropriate next menu step, without interacting with the customer. However, this type of agent assistance is limited in its application. For example, if the customer cannot input their account number, the monitoring agent cannot correct the account number.
Typical solutions today do nothing to encourage or train the customer on how to use the IVR. These present methods do not change the likelihood that a customer will engage a more expensive call center agent when exiting IVR functions. The current solutions create five problems: (1) restarting interactions after the customer abandoned their progress in the IVR; (2) impeding the uptake of the IVR for service delivery (the customer continues to prefer to use a human agent); (3) preventing the customer from learning the IVR system; dissuading organizations from placing more complicated applications on the IVR system because complicated functions have higher user error rates; and (5) propagating the perception that IVR systems are poor service delivery mechanisms.